Subsurface Volume Saturation Modeling via Front Location and Sweep Intensity
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Solution Overview
Problem
Current history matching techniques for subsurface hydrocarbon reservoirs face challenges in accurately and efficiently modeling saturation changes over time, particularly in efficiently handling 3D saturation variation data for solvers like Ensemble Kalman Filter and Ensemble Smoother.
Innovation Solution
A method that transforms observed and simulated saturation data into front location and sweep intensity parameters, allowing for a more efficient mismatch calculation and inversion process by describing cells relative to a fluid front and attributing values based on saturation thresholds, enabling better handling by statistical solvers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional history matching techniques are used to model saturation changes, then the process can be performed with standard solvers, but the accuracy and efficiency of modeling saturation changes over time is insufficient
Solution Approach 1:
The patent transforms the saturation data into two new parameters: front location (binary indicator) and sweep intensity (continuous value). This parameter transformation enables solvers to more accurately and efficiently capture the nonlinear saturation changes by representing them in a form that better reflects the physical processes of fluid front propagation and sweep efficiency.
2Loss of information
If 3D saturation variation data is directly used in history matching, then the complete saturation information is preserved, but the data is difficult to handle efficiently by statistical solvers like Ensemble Kalman Filter and Ensemble Smoother
Solution Approach 1:
The patent segments the saturation data into two distinct components: front location (indicating whether a cell is behind or ahead of the fluid front) and sweep intensity (quantifying the saturation variation magnitude). This segmentation allows statistical solvers to efficiently process the data by separating the discrete front propagation information from the continuous sweep intensity information, while preserving all essential saturation characteristics.
3Manufacturing precision
If conventional mismatch calculation methods are used, then the process is simple to implement, but the model fit accuracy is insufficient
Solution Approach 1:
The patent changes the parameters used in mismatch calculation from direct saturation values to front location and sweep intensity parameters. This transformation improves model fit accuracy by capturing the nonlinear behavior of saturation changes more effectively, while the calculation complexity remains manageable through the use of clear mathematical relationships between the transformed parameters and observed data.
Data Source
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AI summary
Disclosed is a method monitoring changes in saturation of a subsurface volume. The method comprises: obtaining observed data of saturation behaviour from the subsurface volume over time; using one or more models, obtaining simulated data of saturation behaviour from the subsurface volume over time; and transforming each of the observed data and simulated data. The transformation is done such that in each case the data is described in terms of: a front location parameter, wherein a cell of the subsurface volume is attributed a value according to its location relative to a front of the fluid for which saturation is being monitored, and a sweep intensity parameter, wherein a cell of the subsurface volume is attributed a value according to either the observed saturation variation over a time period, or an estimated saturation variation over the time period, finally, a mismatch between saturation behaviour in said transformed observed data and saturation behaviour in said transformed simulated data over said time period is calculated.